HER2 and TOP2A in high-risk early breast cancer patients treated with adjuvant epirubicin-based dose-dense sequential chemotherapy

<p>Abstract</p> <p>Background</p> <p>HER2 and TOP2A parameters (gene status, mRNA and protein expression) have individually been associated with the outcome of patients treated with anthracyclines. The aim of this study was to comprehensively evaluate the prognostic/predictive significance of the above parameters in early, high-risk breast cancer patients treated with epirubicin-based, dose-dense sequential adjuvant chemotherapy.</p> <p>Methods</p> <p>In a series of 352 breast carcinoma tissues from patients that had been post-operatively treated with epirubicin-CMF with or without paclitaxel, we assessed HER2 and TOP2A gene status (chromogenic in situ hybridization), mRNA expression (quantitative reverse transcription PCR), as well as HER2 and TopoIIa protein expression (immunohistochemistry).</p> <p>Results</p> <p>HER2 and TOP2A amplification did not share the same effects on their downstream molecules, with consistent patterns observed in HER2 mRNA and protein expression according to HER2 amplification (all parameters strongly inter-related, p values < 0.001), but inconsistent patterns in the case of TOP2A. TOP2A gene amplification (7% of all cases) was not related to TOP2A mRNA and TopoIIa protein expression, while TOP2A mRNA and TopoIIa protein were strongly related to each other (p < 0.001). Hence, TOP2A amplified tumors did not correspond to tumors with high TOP2A mRNA or TopoIIa protein expression, while the latter were characterized by high Ki67 scores (p = 0.003 and p < 0.001, respectively). Multivariate analysis adjusted for nodal involvement, hormone receptor status, Ki67 score and HER2/TOP2A parameters revealed HER2/TOP2A co-amplification (21.2% of HER2 amplified tumors) as an independent favorable prognostic factor for DFS (HR = 0.13, 95% CI: 0.02-0.96, p = 0.046); in contrast, increased HER2/TOP2A mRNA co-expression was identified as an independent adverse prognostic factor for both DFS (HR = 2.41, 95% CI: 1.31-4.42, p = 0.005) and OS (HR = 2.83, 95% CI: 1.42-5.63, p = 0.003), while high TOP2A mRNA expression was an independent adverse prognostic factor for OS (HR = 2.06, 95% CI: 1.23-3.46, p = 0.006). None of the parameters tested was associated with response to paclitaxel.</p> <p>Conclusions</p> <p>This study confirms the favorable prognostic value of HER2/TOP2A co-amplification and the adverse prognostic value of high TOP2A mRNA expression extending it to the adjuvant treatment setting in early high-risk breast cancer. The strong adverse prognostic impact of high HER2/TOP2A mRNA co-expression needs further validation in studies designed to evaluate markers predictive for anthracyclines.</p> <p>Trial registration</p> <p>Australian New Zealand Clinical Trials Registry <a href="http://www.anzctr.org.au/ACTRN12611000506998">ACTRN12611000506998</a>.</p

Bayesian analysis of two dependent 22 contingency tables

Bayesian analysis of correlated binary data when individual information is not available is considered. In particular, a binary outcome is measured on the same subjects of two independent groups at two separate occasions (usually time points). The groups are formulated through a binary exposure or a prognostic factor. Interest lies in estimating the association between exposure and outcome over time. Standard methods for this purpose apply on the individual item responses and are insufficient in case these are missing. Moreover it is assumed that the only available information is the marginal 22 cross-tabulations between the grouping variable and the response for each occasion. Assuming independent binomial distributions for the two groups, the success probabilities for each occasion as well as the associations between exposure and outcome, based on the corresponding odds ratios, are estimated. In order to deal with the missing information of each item's response and to estimate the corresponding transition probabilities, a Bayesian procedure is adopted.

Volumetric and MGMT parameters in glioblastoma patients: Survival analysis

Abstract Background In this study several tumor-related volumes were assessed by means of a computer-based application and a survival analysis was conducted to evaluate the prognostic significance of pre- and postoperative volumetric data in patients harboring glioblastomas. In addition, MGMT (O6-methylguanine methyltransferase) related parameters were compared with those of volumetry in order to observe possible relevance of this molecule in tumor development. Methods We prospectively analyzed 65 patients suffering from glioblastoma (GBM) who underwent radiotherapy with concomitant adjuvant temozolomide. For the purpose of volumetry T1 and T2-weighted magnetic resonance (MR) sequences were used, acquired both pre- and postoperatively (pre-radiochemotherapy). The volumes measured on preoperative MR images were necrosis, enhancing tumor and edema (including the tumor) and on postoperative ones, net-enhancing tumor. Age, sex, performance status (PS) and type of operation were also included in the multivariate analysis. MGMT was assessed for promoter methylation with Multiplex Ligation-dependent Probe Amplification (MLPA), for RNA expression with real time PCR, and for protein expression with immunohistochemistry in a total of 44 cases with available histologic material. Results In the multivariate analysis a negative impact was shown for pre-radiochemotherapy net-enhancing tumor on the overall survival (OS) (p = 0.023) and for preoperative necrosis on progression-free survival (PFS) (p = 0.030). Furthermore, the multivariate analysis confirmed the importance of PS in PFS and OS of patients. MGMT promoter methylation was observed in 13/23 (43.5%) evaluable tumors; complete methylation was observed in 3/13 methylated tumors only. High rate of MGMT protein positivity (> 20% positive neoplastic nuclei) was inversely associated with pre-operative tumor necrosis (p = 0.021). Conclusions Our findings implicate that volumetric parameters may have a significant role in the prognosis of GBM patients. Furthermore, volumetry could help not only to improve the prediction of outcome but also the outcome itself by identifying patients at high risk of treatment failure and, thus, seek alternative treatment for these patients. In this small series, MGMT protein was associated with less aggressive tumor characteristics.</p

Identification and Validation of a Multigene Predictor of Recurrence in Primary Laryngeal Cancer

Purpose: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. This study attempts to identify and independently validate gene expression models, prognostic of disease-free survival (DFS) in operable laryngeal cancer. Materials and Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 66 patients with laryngeal cancer treated locally with surgery. We applied Cox regression proportional hazards modeling to identify multigene predictors of recurrence. Gene models were then validated in two independent cohorts of 54 and 187 patients (fresh-frozen and formalin-fixed tissue validation sets, respectively). Results: We focused on genes univariately associated with DFS (p&lt;0.01) in the training set. Among several models comprising different numbers of genes, a 30-probe set model demonstrated optimal performance in both the training (log-rank, p&lt;0.001) and 1st validation (p = 0.010) sets. Specifically, in the 1st validation set, median DFS as predicted by the 30-probe set model, was 34 and 80 months for high-and low-risk patients, respectively. Hazard ratio (HR) for recurrence in the high-risk group was 3.87 (95% CI 1.28-11.73, Wald’s p = 0.017). Testing the expression of selected genes from the above model in the 2nd validation set, with qPCR, revealed significant associations of single markers, such as ACE2, FLOT1 and PRKD1, with patient DFS. High PRKD1 remained an unfavorable prognostic marker upon multivariate analysis (HR = 2.00, 95% CI 1.28-3.14, p = 0.002) along with positive nodal status. Conclusions: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. It seems worthy to prospectively validate PRKD1 expression as a laryngeal cancer prognostic marker, for routine clinical applications